Topic: AI Seminar: Owen Rambow
Time: Mar 17, 2021 10:00 AM Eastern Time (US and Canada)
Join Zoom Meeting
https://stonybrook.zoom.us/j/93614644178?pwd=MzJtVDJYYmU5T1dtMzJiUFMxb0x4dz09
Meeting ID: 936 1464 4178. Passcode: 965936
Natural Language Understanding and Semantic Parsing
(Partly joint work with former colleagues at Elemental Cognition)
Semantic parsing refers to the task of determining the propositional content of language: who did what to whom. It is part of the larger task of natural language understanding (NLU). I will start out by discussing what full NLU means, and argue that we are still far away, as a field, from solving full NLU, or even from knowing how to evaluate it.
In the second part of the talk, I will situate semantic parsing in the context of several other NLU subtasks. Typically, the target representation of semantic parsing uses an ontology (such as PropBank or FrameNet). Semantic parsing includes the subtasks of word sense disambiguation, argument detection, and argument role labeling. I will discuss choices among possible target ontologies. I will justify why we created a new ontology, Hector, based on FrameNet and the lexical resource NOAD, and explain some of its characteristics.
In the third part of the talk, I will present experiments we performed using transformer models. We obtain best results using a two-phase model, in which we first choose the frame, and then, given the frame, choose the arguments. We encode the problem for both tasks using indices in the sentence. While we develop the parser for our new ontology Hector, this approach also beats the state of the art for FrameNet and PropBank parsing.Biography: I am a professor in the Department of Linguistics at Stony Brook University with a joint appointment in IACS.
Time: Mar 17, 2021 10:00 AM Eastern Time (US and Canada)
Join Zoom Meeting
https://stonybrook.zoom.us/j/
Meeting ID: 936 1464 4178. Passcode: 965936
Natural Language Understanding and Semantic Parsing
(Partly joint work with former colleagues at Elemental Cognition)
Semantic parsing refers to the task of determining the propositional content of language: who did what to whom. It is part of the larger task of natural language understanding (NLU). I will start out by discussing what full NLU means, and argue that we are still far away, as a field, from solving full NLU, or even from knowing how to evaluate it.
In the second part of the talk, I will situate semantic parsing in the context of several other NLU subtasks. Typically, the target representation of semantic parsing uses an ontology (such as PropBank or FrameNet). Semantic parsing includes the subtasks of word sense disambiguation, argument detection, and argument role labeling. I will discuss choices among possible target ontologies. I will justify why we created a new ontology, Hector, based on FrameNet and the lexical resource NOAD, and explain some of its characteristics.
In the third part of the talk, I will present experiments we performed using transformer models. We obtain best results using a two-phase model, in which we first choose the frame, and then, given the frame, choose the arguments. We encode the problem for both tasks using indices in the sentence. While we develop the parser for our new ontology Hector, this approach also beats the state of the art for FrameNet and PropBank parsing.Biography: I am a professor in the Department of Linguistics at Stony Brook University with a joint appointment in IACS.
Until recently, I was a research scientist at Elemental Cognition. Elemental Cognition is working on deep natural language understanding.
I got my PhD with Aravind Joshi at the University of Pennsylvania in 1994. I have worked at CoGenTex, and at AT&T Labs -- Research, and for many years I was a research scientist at Columbia University in the Center for Computational Learning Systems.